The purpose of this paper is to identify the critical components of a complex system by using survival signature. First, a complex system is abstracted with varying scales and generates a multi-levels model. Then reliability evaluations can be conducted by survival signature from rough to fine for tracing and identifying them. Finally, the feasibility of the proposed approach is demonstrated by an actual production system.
The paper mainly applies a multi-level evaluating strategy for the reliability analysis of complex systems with components of multiple types. In addition, a multi-levels model of a complex system is constructed and survival signature also used for evaluation.
The proposed approach was demonstrated to be the feasibility by an actual production system that is used in the case study.
The case study was performed on a system with simple network structure, but the proposed approach could be applied to systems with complex ones. However, the approach to generate the digraphs of abstraction levels for complex system has to be developed.
So far the approach has been used for the reliability analysis of a machining system. The approach that is proposed for the identification of critical components also can be applied to make maintenance decision.
The multi-level evaluating strategy that was proposed for reliability analysis and the identification of critical components of complex systems was a novel method, and it also can be applied as index to make maintenance planning.
The authors thank the referees for comments on a previous manuscript. The comments led us to significantly improve the paper. This project is also supported by National Natural Science Foundation of China (Grant No. 51875445) and Natural Science Basic Research Plan in Shaanxi Province of China (Program No. 2017ZDJC-21).
Ge, L. and Zhang, Y. (2019), "Multi-level approach for important component identification and reliability evaluation for complex system by survival signature", Engineering Computations, Vol. 37 No. 1, pp. 262-288. https://doi.org/10.1108/EC-01-2019-0031Download as .RIS
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